Modelling accessibility to urban services using fuzzy logic
Bibliographic record
Abstract
Purpose This paper is an attempt to bridge the gap between, on the one hand, the mobility behaviour of households and their perception of accessibility to urban amenities and, on the other hand, house price dynamics as captured through hedonic modelling. Design/methodology/approach In order to analyse the mobility behaviour of individuals and households, their sensitivity to travel time from home to service places is estimated so as to assess their perceived accessibility, using “subjective” indices based on actual trips, as reported in the 2001 origin‐destination survey designed for Quebec City. For comparative purposes, both objective and subjective accessibility indices based, in the former case on observed travel times and, in the latter case on fuzzy logic criteria, are computed and used as a complement to a centrality index in a hedonic model of house prices. Findings Findings indicate that there are statistically significant differences in the way accessibility is structured depending on trip purposes and household profiles. They also suggest that, while an objective measure of accessibility yields good results, resorting to subjective, and more comprehensive, accessibility indices derived from fuzzy logic provides greater insight into the understanding of commuting patterns and travel behaviour of people. Practical implications Better understanding the complexity of individuals’ and households’ mobility behaviour should result in more adequate initiatives and decisions being taken by transportation and city planning authorities. Originality/value Accessibility to jobs and services has long been known as a major determinant of urban, residential and non residential, rents. Yet, it is more often than not assumed to derive from a rather straightforward process, which this paper shows is not the case.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".